1. Field of the Invention
The present invention generally relates to the passive detection of signals which may be transmitted acoustically or electromagnetically to a detection location and, more particularly, to detection and spectrum analysis of signals in the presence of high levels of noise, such as may be encountered with hydrophones or in condition-based diagnostics of machinery as well as active detectors such as pulse Doppler radar.
2. Description of the Prior Art
Many arrangements for detection and enhancement of a signal in the presence of noise are well-known in the art; radio and television receivers being particularly familiar examples. Coherent radar is another application in which enhancement of a signal together with rejection of background noise and time-varying clutter is particularly critical. In all of these systems and others, however, some parameters of the signal to be detected, such as the carrier frequency of the signal of interest, are known.
When this is not the case, such as in condition-based diagnostics where slight changes in the noise output of a complex machine may include one or more frequency characteristics which are specific to a potential malfunction, and it is desired to detect a completely unknown acoustic or electromagnetic signal in the presence of noise, the classical technique has employed spectrum analysis. In this technique, discussed in detail in "The use of Fast Fourier Transform for the Estimation of Power Spectra: A Method Based on Time averaging over Short, Modified Periodograms" by P. D. Welsh, IEEE Transactions on Audio Electroacoustics, Vol. AU-15, pp. 70-73, June, 1967, which is hereby fully incorporated by reference, a tonal or sine-wave signal in a receiver output having low signal to noise ratio (SNR) is analyzed at varying resolutions (e.g., bandwidths) to look for peaks which increase as bandwidth is reduced (e.g. as resolution is increased). If a signal is present having a frequency falling within one of a plurality of overlapping bandwidths, decrease of bandwidth will reduce the relative signal power attributable to noise, leaving substantially only the signal power in the tonal.
This approach has three principal drawbacks, however. The methodology is inherently slow or hardware intensive since a reduction of bandwidth by any given factor increases the number of bands which must be processed by the same factor for any given resolution. Since the process is carried out sequentially at a plurality of resolutions, processing time or hardware (whether analog or digital) must be greatly multiplied as resolution increases. Further, since the signal of interest may vary in frequency due to modulation of frequency or Doppler effects (if either or both of the source or receiver are in motion), the signal power of the signal of interest may be distributed over several bands as resolution is increased. Additionally, to increase spectral resolution, known spectrum analysis techniques must increase the amount of data available which, in turn, increases processing time.
Higher-Order Statistics (HOS) methods have been recently employed in coherent radar systems for object profiling and velocity measurement. Specifically, U.S. Pat. Nos. 5,227,801, and 5,231,403, to Robert D. Pierce which are hereby fully incorporated by reference, describe particularly effective techniques of achieving these goals. Even more recently, a technique of detecting moving and even accelerating targets with coherent radar and HOS techniques has been described in U.S. patent application Ser. No. 08/127,619, filed Sep. 28, 1993 now U.S. Pat. No. 5,402,131 issued Mar. 28, 1995, (Navy case No. 75,280) by Robert D. Pierce, which is also fully incorporated herein by reference. HOS methods have several desirable characteristics of preserving phase information (e.g., coherency), are insensitive to linear phase shifts and suppress Gaussian noise effects.
While HOS methods are used to enhance signals in radar systems, some aspects of the signals to be detected are necessarily known, as pointed out above. To date, no system has significantly increased the noise rejection of the classical technique of signal detection, described above, for an unknown signal.
It is also generally recognized that a desired signal can often be detected under adverse conditions such as high noise levels if certain adaptations are made in the detector, based on the expected nature of the noise and/or the signal. However, just as small variations in the frequency of a signal can defeat or greatly reduce the effectiveness of known spectrum analysis-based detectors, a detector which is specifically adapted to certain signal characteristics is generally ineffective to detect signals having characteristics which are only slightly at variance therewith. Moreover, there is currently no consistent methodology or single apparatus capable of detecting a wider variety of signal variation than the spectrum analysis-based devices and methods described above which remains the methodology of choice where the characteristics of the signal to be detected are entirely unknown. Conversely, no technique has heretofore been developed to broaden the range of signal variation which will allow detection of a signal by a signal analyzer.